Prediction and identification of CD4+ T cell epitope for the protective antigens of Mycobacterium tuberculosis

Abstract

CD4+T cell epitopes plays a key role in anti-tuberculosis (TB) immunity, CD4+T cell epitopes suitable for the domestic population are lacking. Therefore, we predicted and identified novel CD4+T cell epitopes. The bioinformatics software, namely, DNAStar (DNASTAR of the United States), SYFPEITHI (INTERFACTORS INSTITUT Für ZELL Biologie of Germany), RANKPEP, and NetMHC IIpan (National Cancer Institute, United States of America), were used to comprehensively predict the CD4+T cell immune epitope of Mycobacterium TB, and the predicted epitope polypeptide was synthesized by the standard Fmoc scheme. The proliferation of PBMC and CD4+T cells stimulated by peptides was preliminarily detected by the CCK8 method. Then, the candidate polypeptides screened out by the CCK8 method were verified again by the BrdU assay, and flow cytometry was performed to analyze further the extent of their stimulation on the proliferation of CD4+T cells. The changes in the secreted cytokines IFN-γ, TNF-α, IL-2, and IL-10 before and after the candidate polypeptide stimulation of CD4+T lymphocytes were detected by ELISA. The preliminary humoral immunity test was conducted by indirect ELISA to evaluate the serological diagnostic value of the CD4+T cell epitope polypeptide. In this study, 5 novel candidate CD4+T cell epitope polypeptides with the amino acid sequences of LQGQWRGAAGTAAQA, PVTLAETGSTLLYPL, AAAWGGSGSEAYQGV, QFVYAGAMSGLLDPS, and KAALTRTASNMNAAA and others that have not been reported in the research were predicted. For convenience, the 5 candidates were successively named as P 39 , P 50 , P 40 , P 185 , and P 62 . P 39 , P 62 , and the mixed peptide P 39 +P 62 could effectively induce the proliferation of CD4+T cells and increase the secretion of IFN-γ, TNF-α, and IL-2 from the CD4+T cells, while reducing the content of IL-10. The serological test showed that the sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) of P 39 were 75%, 67.71%, and 0.844, respectively. The sensitivity, specificity, and AUC of P 62 were 91.66%, 46.87%, and 0.649, respectively. The sensitivity of the mixed peptide P 39 +P 62 was 95.83%, the specificity was 97.91%, and the AUC was 0.793. The P 39 and P 62 polypeptides were predicted and identified as potential CD4+T cell immune epitope polypeptides of M. TB. The polypeptide had better diagnosis effect, which provided potential candidate epitope polypeptides for the development of TB-specific diagnosis reagents and novel TB epitope vaccines.

Viral Load and CD4+ Markers as Determinants of Tuberculosis Coinfection Among People Living with HIV/AIDS in Papua Indonesia

“…19 Based on the protective mechanism of anti-TB immunity, the epitope on CD4 + T cells plays a key role in the process of stimulating the CD4 + T immune response. 20…”

“…19 Based on the protective mechanism of anti-TB immunity, the epitope on CD4 + T cells plays a key role in the process of stimulating the CD4 + T immune response. 20 HIV infection significantly suppresses the systemic proinflammatory cytokine response induced by M. tuberculosis. The course of the disease from Latent tuberculosis infection to pulmonary TB (PTB) in HIV infection may not only be due to depletion of CD4 + T cell counts but also a disturbance in CD4 + T cell function specific to M. Tuberculosis.…”

“…7 However, the annual risk of active TB in people with TB-HIV coinfection is 5-15%. 6 It is estimated that PLHIV is 18 (15)(16)(17)(18)(19)(20)(21) times more at risk of developing TB than people without HIV. 1 TB-HIV coinfection also has a high case fatality rate and a lifetime risk.…”

Use of recombinant proteins in the diagnosis of sexually transmitted infections: a systematic review and meta-analysis

“…Accordingly, computational biology, which involves mining and extracting information from genomes deposited in databases, is an important area for uncovering important information on antigens of several pathogens (J. Liu et al, 2021). The prediction of antigens from gene sequences that may be good targets in Research, Society andDevelopment, v. 11, n. 10, e433111032974, 2022 (CC BY 4.0) | ISSN 2525-3409 | DOI: http://dx.doi.org/10.33448/rsd-v11i10.32970 silico to develop recombinant antigens is a valuable approach for producing sensitive antibodies against different subtypes and populations of a given pathogen (Barbosa et al, 2020).…”